As a result of increases in the elderly population, it is expected that the number of patients with neurodegenerative disorders involving forms of dementia such as Alzheimer's disease will increase. Because these diseases progress with age and affect both the patient and their living environment, it is important to diagnose such cases at an early stage.
Such neurodegenerative disorders involving dementia are diagnosed by applying the results of, for example, neuropsychological tests, including the well-known Mini Mental Status Examination (hereinafter referred to as “MMSE”), as well as interviews and clinical findings, etc. to diagnostic criteria such as DSM-III-R or ICD-10. These diagnoses do not necessarily have high specificity. So these diagnoses are combined with diagnostic imaging such as CT, MRI, or SPECT in order to improve the diagnostic accuracy rate. However, even when diagnostic imaging such as CT, MRI, or SPECT is involved, because the diagnostic accuracy of diagnostic imaging depends on the level of proficiency and the subjectivity of the radiography interpreter, there is a problem in that the results vary between facilities and examiners. Accordingly, there has been a desire for techniques allowing for neurodegenerative disorders to be detected in a more objective manner.
Recent studies have shown that in cases of neurodegenerative disorders involving dementia, brain functions such as cerebral blood flow and glucose metabolic rate become partially deteriorated (See below Non-patent Document 1). Using this knowledge, The below Non-patent Document 2 discloses a method of using positron-emission tomography (hereinafter referred to as “PET”) images obtained by administering the glucose metabolism tracer 2-[18F]fluoro-2-deoxy-D-glucose (hereinafter referred to as “FDG”) to conduct comparisons with a healthy group, calculate the t-values of the pixel values for each pixel, and discriminate between Alzheimer's disease patients and healthy subjects.
Further, International Publication No. 2007/063656 discloses methods for objectively detecting images based on neurodegenerative disorders at an early stage by calculating t-values or z-scores based on comparisons with a healthy subject database for pixels within a preset region of interest in a subject image, and defining a fixed threshold value for the obtained t-values or z-scores (Patent Document 1).